Purpose

Rupture of a cerebral aneurysm causes subarachnoidal hemorrhage,
which is fatal in up to 50% of the cases.
Information about size,
location and shape of aneurysms is crucial for optimal treatment.
Measurements that are performed directly on 2D images obviously result in inadequate diameters that depend on the image slicing axis.
The process of retrieving an adequate 3D measurement of an aneurysm is very time consuming and must comprise the following tasks: 3D reconstruction of the vessel...

Methods and Materials

We have developedthe software system MEDVIS 3D ( www.medvis3d.at ) [2] that is capable of accomplishing all necessary tasks (described in section Purpose) for an automated aneurysm assessment.
After a 3D reconstruction of 2D medical imaging data (see fig.
5) a 3D thinning algorithm [4] is applied to the 3D volume to extract the centerline (skeleton) of the cerebral vessel structure (see fig.
5+6).
For each centerline point the corresponding vessel diameter is calculated.
Based on the skeleton...

Results

We tested our algorithm on 21 medical image data sets (DSA series 256x256x400) which were provided and evaluated by our medical partners with the following contents: 14 datasets contained exactly one aneurysm, 4 datasets contained two aneurysms, one contained three aneurysms, and 2 datasets didn't contain any aneurysm. All datasets together showed 25 aneurysms,
21 of which were detected correctly,
which gives a sensitivity of 76%.
6 aneurysms were not detected correctly.
Three of these...

Conclusion

Our results show that automatic aneurysm detection based on the extracted vessel center line yields accurate and comparable measurements.
Moreover,
our software MEDVIS 3D allows to retrieve the segmented aneurysm from the 2D images with only few mouse clicks.
The resulting diameters can be transferred to a central database for later review and analysis. Additonally,
we have developed a blood flow simulation system [1] based on the Finite Element Method (FEM) that can automatically calculate...